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Efficient Symmetry Breaking for SAT-Based Minimum DFA Inference

Part of the Lecture Notes in Computer Science book series (LNTCS,volume 11417)


Inference of deterministic finite automata (DFA) finds a wide range of important practical applications. In recent years, the use of SAT and SMT solvers for the minimum size DFA inference problem (MinDFA) enabled significant performance improvements. Nevertheless, there are many problems that are simply too difficult to solve to optimality with existing technologies. One fundamental difficulty of the MinDFA problem is the size of the search space. Moreover, another fundamental drawback of these approaches is the encoding size. This paper develops novel compact encodings for Symmetry Breaking of SAT-based approaches to MinDFA. The proposed encodings are shown to perform comparably in practice with the most efficient, but also significantly larger, symmetry breaking encodings.


  • DFA inference
  • Boolean satisfiability
  • Symmetry breaking

IZ was supported by RFBR (project 18-37-00425). AM, AI and JMS were supported by FCT grants ABSOLV (PTDC/CCI-COM/28986/2017), FaultLocker (PTDC/CCI-COM/29300/2017), SAFETY (SFRH/BPD/120315/2016), and SAMPLE (CEECIND/04549/2017). VU was supported by the Government of Russia (Grant 08-08).

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    The encoding size shown is adapted from the results in [20], taking into account that both \(|T^{+}|\) and \(|T^{-}|\) can grow with \(N=|T|\). The size of \(|\varSigma |\) is assumed constant.

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Zakirzyanov, I., Morgado, A., Ignatiev, A., Ulyantsev, V., Marques-Silva, J. (2019). Efficient Symmetry Breaking for SAT-Based Minimum DFA Inference. In: Martín-Vide, C., Okhotin, A., Shapira, D. (eds) Language and Automata Theory and Applications. LATA 2019. Lecture Notes in Computer Science(), vol 11417. Springer, Cham.

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